whisper-large-v3-turbo-fa-c13-avs

This model is a fine-tuned version of openai/whisper-large-v3-turbo on the Common Voice 13.0 dataset. It achieves the following results on the evaluation set:

• Loss: 0.2687
• Wer: 27.9267

Model description

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

• learning_rate: 1e-05
• train_batch_size: 16
• eval_batch_size: 8
• seed: 42
• optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• lr_scheduler_type: linear
• lr_scheduler_warmup_steps: 500
• training_steps: 5000
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.2167	0.4160	1000	0.4101	39.1360
0.1643	0.8319	2000	0.3560	34.6257
0.0874	1.2479	3000	0.3249	32.9962
0.0873	1.6639	4000	0.2836	29.3890
0.0421	2.0799	5000	0.2687	27.9267

Framework versions

• Transformers 4.52.1
• Pytorch 2.7.0+cu126
• Datasets 3.6.0
• Tokenizers 0.21.1

Notes

• Amir Nezami safa
• Vahid Mahmodiyan
• Shahab Salehi